Author

M. Tessmer

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Biophysics· 4

Signature Assays, Organisms & Methods

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Approach:deep learning· 3 Research Focus:protein folding & dynamics· 3 Assay:fluorescence / live-cell microscopy· 2 Approach:statistical model· 2 Research Focus:benchmarking· 1 Assay:electronic health records· 1 Approach:experimental assay· 1 Research Focus:protein structure prediction· 1

Frequent Co-Authors

S. Stoll· 3 shared E. G. Evans· 2 shared J. Petersson· 2 shared K. D. Shaffer· 2 shared S. E. Gordon· 2 shared W. N. Zagotta· 2 shared D. del Alamo· 1 shared H. S. Mchaourab· 1 shared

Activity by Year

2019-2023 · peak 3/yr

Co-Author Collaboration Network

10 top collaborators · 21 mutual co-author links

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3 shared papersBiophysics

S. Stoll

Mutual co-authors in cluster

Author profile →

4 papers

Recent·Most cited

Long-distance tmFRET using bipyridyl- and phenanthroline-based ligands

S. E. Gordon, E. G. Evans, S. C. Otto, M. Tessmer, K. D. Shaffer, M. T. Gordon, J. Petersson, S. Stoll, W. N. Zagotta

This paper expands the working distance of tmFRET to 50 Å using new ligands, enabling precise measurement of conformational changes in maltose binding protein under physiological conditions.

bioRxiv · Oct 9, 2023Biophysics

Measuring conformational equilibria in allosteric proteins with time-resolved tmFRET

W. N. Zagotta, E. G. Evans, P. Eggan, M. Tessmer, K. D. Shaffer, J. Petersson, S. Stoll, S. E. Gordon

This paper develops a fluorescence method to measure protein conformational dynamics and energetics using time-resolved tmFRET and validates it with EPR spectroscopy.

bioRxiv · Oct 9, 2023Biophysics

A novel approach to modeling side chain ensembles of the bifunctional spin label RX

M. Tessmer, S. Stoll

The paper introduces a method to model side chain ensembles of bifunctional spin labels using rotamer libraries and validates it against experimental data.

bioRxiv · May 24, 2023 · PreprintBiophysics

Protein fold prediction using simulated DEER distance distributions and decay traces

D. del Alamo, M. Tessmer, R. A. Stein, J. B. Feix, H. S. Mchaourab, J. Meiler

This paper introduces RosettaDEER, a method that simulates DEER distance distributions and decay traces to improve protein fold prediction using sparse experimental data.

bioRxiv · Mar 18, 2019 · PreprintBiophysics